统计信号分析与处理 2016 大作业选题

 大作业报告提交时间初步定为6月中旬， 提交形式为：报告（PDF格式最佳）+仿真代码，请大家大家提前准备。

分数：

15分。

任务：

2~3人一组，选择一篇paper，读懂，做出仿真，并提交一份报告。paper可以可以自行选择，也可以从下面链接中给出的文章中里选。

选题方法：

请同学们在评论中回复自己队的队员的姓名与学号和要选的文章的编号，每篇文章仅限一组，按回复先后顺序进行确认。

如果助教回复确认，表示选题成功。

已选题目的信息会及时在课程主页进行更新。

示例回复：

选题[15]

张三 PB14066001

李四 PB14066002

格式不清的回复无法进行确认。，我会在大作业页面更新已经被选的题目。

课堂presentation：

考试前后会安排时间做presentation，各组用slides展示自己的成果。该项为选做，做的话会有额外加分，加分后的总分可能超过15分。

提供76篇备选paper：

下载地址：http://home.ustc.edu.cn/~dw13/slides2016/paper2016.zip 


如另有通知，请关注课程主页：http://home.ustc.edu.cn/~dw13/homepage2016.html

论文题目如下：
[1] iterative convex refinement for sparse recovery

[2] optimal noise benefits in neyman-pearson and inequality-constrained statistical signal detection

[3] separating function estimation tests a new perspective on binary composite hypothesis testing

[4] speech enhancement with nonstationary acoustic noise detection in time domain

[5] optimaldistributedminimum-variancebeamforming approaches for speech enhancement in wireless acoustic sensor networks

[6] state of the art in statistical methods for language and speech processing

[7] quadratically constrained minimum dispersion beamforming for non-gaussian signals via gradient projection

[8] a hybrid technique for blind separation of non-gaussian and time-correlated sources using a multicomponent approach

[9] speaker recognition by machines and humans_ a tutorial review

[10] randomized sensor selection in sequential hypothesis testing

[11] interference-plus-noise covariance matrix reconstruction via spatial power spectrum sampling for robust adaptive beamforming

[12] tensor decompositions for signal processing applications

[13] threshold setting for adaptive matched filter and adaptive coherence estimator

[14] robust adaptive beamforming based on interference covariance matrix reconstruction and steering vector estimation

[15] acoustic recognition of multiple bird species based on penalized maximum likelihood

[16] toward discovery of the artist's style_ learning to recognize artists by their artworks

[17] sequential bayesian sparse signal reconstruction using array data

[18] iterative robust minimum variance beamforming

[19] a rank-one tensor updating algorithm for tensor completion

[20] k-svd an algorithm for designing overcomplete dictionaries for sparse representation

[21] a new parametric glrt for multichannel adaptive signal detection

[22] norm constrained capon beamforming using multi-rank signal models with kalman filter implementation

[23] maximally robust capon beamformer

[24] rank-constrained separable semidefinite programming with applications to optimal beamforming

[25] robust adaptive beamforming based on steering vector estimation with as little as possible prior information

[26] fast signal separation of 2-d sparse mixture via approximate message-passing

[27] doubly constrained robust capon beamformer with ellipsoidal uncertainty sets

[28] optimal widely linear mvdr beamforming for noncircular signals

[29] optimizing speech intelligibility in a noisy environment_ a unified view

[30] supervised monaural speech enhancement using complementary joint sparse representations

[31] acoustic scene classification_ classifying environments from the sounds they produce

[32] new conditional posterior cramér-rao lower bounds for nonlinear sequential bayesian estimation

[33] on the invariance, coincidence, and statistical equivalence of the glrt, rao test, and wald test

[34] linking speech enhancement and error concealment based on recursive mmse estimation

[35] sequential detection with mutual information stopping cost

[36] dictionary learning for blind one bit compressed sensing

[37] robust adaptive beamforming for general rank signal model with positive semidefinite constraint via potdc

[38] generalized iterated kalman filter and its performance evaluation

[39] decision fusion for image quality assessment using an optimization approach

[40] distributed compressed sensing off the grid

[41] distributed detection over channels with memory

[42] generalized nested sampling for compressing low rank toeplitz matrices

[43] a new robust estimation method for arma models

[44] sensitivity analysis of likelihood ratio test in  distributed and or gaussian noise

[45] joint learning of multiple regressors for single image super-resolution

[46] minimum dispersion beamforming for non-gaussian signals

[47] performance analysis of spatial smoothing schemes in the context of large arrays

[48] a repeated significance test with applications to sequential detection in sensor networks

[49] robust adaptive beamforming in partly calibrated sparse sensor arrays

[50] adaptive detection and estimation in the presence of useful signal and interference mismatches

[51] on low complexity robust beamforming with positive semidefinite constraints

[52] widely linear mvdr beamformers for the reception of an unknown signal corrupted by noncircular interferences

[53] a simple sampler for the horseshoe estimator

[54] adaptive detection of a partly known signal corrupted by strong interference

[55] optimal adaptive waveform design for cognitive mimo radar

[56] adaptive widely linear reduced-rank interference suppression based on the multistage wiener filter

[57] compositional models for audio processing_uncovering the structure of sound mixtures

[58] maximum likelihood acoustic factor analysis models for robust speaker verification in noise

[59] effective binaural multi-channel processing algorithm for improved environmental presence

[60] beamforming via nonconvex linear regression

[61] robust adaptive beamforming using multidimensional covariance fitting

[62] cfar detection strategies for distributed targets under conic constraints

[63] on the computational intractability of exact and approximate dictionary learning

[64] countering radio frequency interference in single-sensor quadrupole resonance

[65] parametric spatial sound processing_ a flexible and efficient solution to sound scene acquisition, modification, and reproduction

[66] sparse inverse covariance estimation

[67] opportunistic beamforming with wireless powered 1-bit feedback through rectenna array

[68] maximum likelihood estimation from uncertain data in the belief function framework

[69] robust sparse blind source separation

[70] adaptive uncertainty bas
4000
ed iterative robust capon beamformer using steering vector mismatch estimation

[71] non-parametric detection of the number of signals hypothesis testing and random matrix theory

[72] fast sparse period estimation

[73] robust adaptive beamforming using a low-complexity shrinkage-based mismatch estimation algorithm

[74] a compressed sensing approach to blind separation of speech mixture

[75] eigenvalue beamforming using a multirank mvdr beamformer and subspace selection